EDA

library(tidyverse)

library(paletteer)
paletteer_d("LaCroixColoR::Pamplemousse")

## <colors>
## #EA7580FF #F6A1A5FF #F8CD9CFF #1BB6AFFF #088BBEFF #172869FF

rawdata = read_csv("data/mental_health.csv") |> 
  janitor::clean_names() |>
  mutate(indicator = str_replace(indicator, ", Last 4 Weeks", "")) |> 
  select(-phase,-quartile_range,-suppression_flag) |> 
  mutate(group = str_replace(group, "By", ""))|> 
  select(start_date=time_period_start_date,end_date=time_period_end_date,everything()) 

tidydata=rawdata |> 
  mutate(start_dates=mdy(pull(rawdata, start_date)),
         end_dates=mdy(pull(rawdata, end_date)))|> 
        mutate(tpl=time_period_label) |>  
        mutate(year = as.numeric(str_extract(tpl, "\\d{4}")))|> 
         separate(col=time_period_label, into=c("month_period_label","years"), sep = ", ", remove = FALSE,extra="merge") |> 
  select(-time_period_label,-start_date,-end_date) |>
  mutate(week_number=time_period-12) |> select(indicator,year,start_dates,end_dates,week_number,month_period_label,group,state,subgroup,value,low_ci,high_ci,confidence_interval)

EDA

My graphs: Differences in indicator variables by gender, sexuality, race/ethnicity

Gender

tidydata |>
  filter(group == " Sex", state == "United States") |>
  group_by(month_period_label, subgroup, indicator) |>
  ggplot(aes(x = week_number, y = value, color = indicator)) +
  geom_line() +
  facet_grid(. ~ subgroup) +
  scale_x_continuous(limits = c(1, 33)) +
  theme_gray() +
  theme(legend.position = "bottom")

## Warning: Removed 20 rows containing missing values (`geom_line()`).

tidydata |>
  filter(group == " Sex", state == "United States") |>
  group_by(month_period_label, subgroup, indicator) |>
  ggplot(aes(x = week_number, y = value, color = subgroup)) +
  geom_line() +
  facet_grid(. ~ indicator) +
  scale_x_continuous(limits = c(1, 33)) +
  theme_gray() +
  theme(legend.position = "bottom")

## Warning: Removed 10 rows containing missing values (`geom_line()`).

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

tidydata |>
  filter(group == " Sex", state == "United States", indicator == "Took Prescription Medication for Mental Health And/Or Received Counseling or Therapy") |>
  group_by(year, indicator, subgroup) |>
  summarize(mean_value = mean(value, na.rm = TRUE)) |>
  plot_ly(x = ~year, y = ~mean_value, color = ~subgroup, type = "bar") |>
  layout(
    xaxis = list(title = "Week"),
    yaxis = list(title = "Percent"))

## `summarise()` has grouped output by 'year', 'indicator'. You can override using
## the `.groups` argument.

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

Sexuality

tidydata |>
  filter(group == " Sexual orientation", state == "United States") |>
  group_by(month_period_label, subgroup, indicator) |>
  ggplot(aes(x = week_number, y = value, color = subgroup)) +
  geom_line() +
  facet_grid(. ~ indicator) +
  scale_x_continuous(limits = c(24, 33)) +
  theme_grey() +
  theme(legend.position = "bottom")

## Warning: Removed 9 rows containing missing values (`geom_line()`).

tidydata |>
  filter(group == " Sexual orientation", state == "United States") |>
  group_by(month_period_label, subgroup, indicator) |>
  ggplot(aes(x = week_number, y = value, color = indicator)) +
  geom_line() +
  facet_grid(. ~ subgroup) +
  scale_x_continuous(limits = c(24, 33)) +
  theme_grey() +
  theme(legend.position = "bottom")

## Warning: Removed 12 rows containing missing values (`geom_line()`).

Race/ethnicity

tidydata |>
  filter(group == " Race/Hispanic ethnicity", state == "United States") |>
  group_by(month_period_label, subgroup, indicator) |>
  ggplot(aes(x = week_number, y = value, color = subgroup)) +
  geom_line() +
  facet_grid(. ~ indicator) +
  scale_x_continuous(limits = c(1, 33)) +
  theme_grey() +
  theme(legend.position = "bottom")

## Warning: Removed 25 rows containing missing values (`geom_line()`).

tidydata |>
  filter(group == " Race/Hispanic ethnicity", state == "United States") |>
  group_by(month_period_label, subgroup, indicator) |>
  ggplot(aes(x = week_number, y = value, color = indicator)) +
  geom_line() +
  facet_grid(. ~ subgroup) +
  scale_x_continuous(limits = c(1, 33)) +
  theme_grey() +
  theme(legend.position = "bottom")

## Warning: Removed 20 rows containing missing values (`geom_line()`).